Motivated by a clinical trial conducted by Janssen Pharmaceutica in which a flexible dosing regimen is compared to placebo, we evaluate how switchers in the treatment arm (i.e., patients who were switched to the higher dose) would have fared had they been kept on the low dose. This is done in order to understand whether flexible dosing is potentially beneficial for them. Simply comparing these patients' responses with those of patients who stayed on the low dose does not likely entail a satisfactory evaluation because the latter patients are usually in a better health condition. Because the available information in the considered trial is too limited to enable a reliable adjustment, we will instead transport data from a fixed dosing trial that has been conducted concurrently on the same target, albeit not in an identical patient population. In particular, we propose an estimator that relies on an outcome model, a model for switching, and a propensity score model for the association between study and patient characteristics. The proposed estimator is asymptotically unbiased if either the outcome or the propensity score model is correctly specified, and efficient (under the semiparametric model where the randomization probabilities are known and independent of baseline covariates) when all models are correctly specified. The proposed method for transporting information from an external study is more broadly applicable in studies where a classical confounding adjustment is not possible due to near positivity violation (e.g., studies where switching takes place in a (near) deterministic manner). Monte Carlo simulations and application to the motivating study demonstrate adequate performance.

中文翻译：

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在随机临床试验中对切换者剂量切换效果的有效、双重稳健估计

受 Janssen Pharmaceutica 进行的一项临床试验的启发，该试验将灵活的给药方案与安慰剂进行了比较，我们评估了治疗组中的转换者（即转换到更高剂量的患者）如果保持低剂量，他们的表现如何剂量。这样做是为了了解灵活的剂量是否对他们有潜在的好处。简单地将这些患者的反应与保持低剂量的患者的反应进行比较，不太可能得到令人满意的评价，因为后者的健康状况通常较好。由于所考虑试验中的可用信息太有限，无法进行可靠的调整，因此我们将转而传输针对同一目标同时进行的固定剂量试验的数据，尽管不是在相同的患者人群中进行的。特别是，我们提出了一个依赖于结果模型、转换模型和研究与患者特征之间关联的倾向评分模型的估计器。如果正确指定了结果或倾向评分模型，则建议的估计量是渐近无偏的，并且在正确指定所有模型时有效（在随机概率已知且独立于基线协变量的半参数模型下）。从外部研究中传输信息的建议方法更广泛地适用于由于接近正性违反而无法进行经典混杂调整的研究（例如，以（接近）确定性方式进行切换的研究）。